All-perovskite tandem solar cells with 3D/3D bilayer perovskite heterojunction.

All-perovskite tandem solar cells promise higher power-conversion efficiency (PCE) than single-junction perovskite solar cells (PSCs) while maintaining a low fabrication cost1-3. However, their performance is still largely constrained by the subpar performance of mixed lead-tin (Pb-Sn) narrow-bandgap (NBG) perovskite subcells, mainly because of a high trap density on the perovskite film surface4-6. Although heterojunctions with intermixed 2D/3D perovskites could reduce surface recombination, this common strategy induces transport losses and thereby limits device fill factors (FFs)7-9. Here we develop an immiscible 3D/3D bilayer perovskite heterojunction (PHJ) with type II band structure at the Pb-Sn perovskite-electron-transport layer (ETL) interface to suppress the interfacial non-radiative recombination and facilitate charge extraction. The bilayer PHJ is formed by depositing a layer of lead-halide wide-bandgap (WBG) perovskite on top of the mixed Pb-Sn NBG perovskite through a hybrid evaporation-solution-processing method. This heterostructure allows us to increase the PCE of Pb-Sn PSCs having a 1.2-µm-thick absorber to 23.8%, together with a high open-circuit voltage (Voc) of 0.873 V and a high FF of 82.6%. We thereby demonstrate a record-high PCE of 28.5% (certified 28.0%) in all-perovskite tandem solar cells. The encapsulated tandem devices retain more than 90% of their initial performance after 600 h of continuous operation under simulated one-sun illumination.

Neuromelanin-sensitive MRI of the substantia nigra distinguishes bipolar from unipolar depression.

Depression in bipolar disorder (BD-II) is frequently misdiagnosed as unipolar depression (UD) leading to inappropriate treatment and downstream complications for many bipolar sufferers. In this study, we evaluated whether neuromelanin-MR signal and volume changes in the substantia nigra (SN) can be used as potential biomarkers to differentiate BD-II from UD. The signal intensities and volumes of the SN regions were measured, and contrast-to-noise ratio (CNR) to the decussation of the superior cerebellar peduncles were calculated and compared between healthy controls (HC), BD-II and UD subjects. Results showed that compare to HC, both BD-II and UD subjects had significantly decreased CNR and increased volume on the right and left sides. Moreover, the volume in BD-II group was significantly increased compared to UD group. The area under the receiver operating characteristic curve (AUC) for discriminating BD from HC was the largest for the Volume-L (AUC, 0.85; 95% confidence interval [CI]: 0.77, 0.93). The AUC for discriminating UD from HC was the largest for the Volume-L (AUC, 0.76; 95% CI: 0.65, 0.86). Furthermore, the AUC for discriminating BD from UD was the largest for the Volume-R (AUC, 0.73; 95% CI: 0.62, 0.84). Our findings suggest that neuromelanin-sensitive magnetic resonance imaging techniques can be used to differentiate BD-II from UD.

Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.

BACKGROUND: The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity. METHODS: A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain ß coefficients, construct predictive models and nomogram incorporating MRI morphological features in the training cohort, and validated in the validation cohort. The discrimination, calibration, and decision curve analysis of the nomogram were performed. The diagnosis efficacy, area under the curve (AUC) and net reclassification index (NRI) were calculated and compared with TI-RADS. RESULTS: 572 thyroid nodules were included (training cohort: n = 397, validation cohort: n = 175). Age, low signal intensity on T2WI, restricted diffusion, reversed halo sign in delay phase, cystic degeneration and wash-out pattern were independent predictors of malignancy. The nomogram demonstrated good discrimination and calibration both in the training cohort (AUC = 0.972) and the validation cohort (AUC = 0.968). The accuracy, sensitivity, specificity, PPV, NPV and AUC of MRI-based prediction were 94.4%, 96.0%, 93.4%, 89.9%, 96.5% and 0.947, respectively. The MRI-based prediction model exhibited enhanced accuracy (NRI>0) in comparison to TI-RADSs. CONCLUSIONS: The prediction model for diagnosis of benign and malignant thyroid nodules demonstrated a more notable diagnostic efficacy than TI-RADS. Compared with the TI-RADSs, predictive model had better specificity along with a high sensitivity and can reduce overdiagnosis and unnecessary biopsies.

Examining the cross-sectional relationship of platelet/high-density lipoprotein cholesterol ratio with depressive symptoms in adults in the United States.

AIMS: Herein, we examined the correlation between platelet/high-density lipoprotein cholesterol ratio (PHR) and symptoms of depression among United States adults. METHODS: Data acquired from the 2007-2018 National Health and Nutrition Examination Survey, involving individuals ≥ 20 years of age, with available PHR and depression diagnosis information. We employed weighted uni- and multivariable logistic regression analyses to assess the distinct correlation between PHR and depressive symptoms. Additionally, we conducted subgroup, interaction, and restricted cubic spline analyses. RESULTS: In all, 28,098 subjects were recruited for analysis, with 8.04% depression status and 19.31 ± 0.11 mean PHR value. Depressive symptoms increased with higher quartiles of PHR. Following fully confounder adjustments in model 2, participants with the largest PHR quartiles exhibited a 53% (OR: 1.53, 95%CI: 1.00-2.33, P = 0.05) raised depressive symptoms, relative to participants with least PHR quartiles. Based on the two-piece-wise regression, the breakpoint was PHR = 23.76, and a positive association was more evident when PHR < 23.76 (OR = 1.06, 95%CI: 1.02-1.10, P = 0.01). When PHR ≥ 23.76, the correlation disappeared (P = 0.85). Using subgroup and interaction analyses, we revealed a positive relationship between PHR and depressive symptoms almost consistent among various population settings. CONCLUSIONS: A convenient biomarker, the PHR was independently associated with an increased risk of depressive symptoms and may be a promising new bioindicator for the prediction of depression diagnosis.

Clinical and ultrasonic risk factors for high-volume central lymph node metastasis in cN0 papillary thyroid microcarcinoma: A retrospective study and meta-analysis.

OBJECTIVE: Papillary thyroid microcarcinoma (PTMC) comprises more than 50% of all newly detected cases of papillary thyroid carcinoma (PTC). High-volume lymph node metastasis (involving >5 lymph nodes) (hv-LNM) is associated with PTMC recurrence. In half of the clinically node-negative (cN0) PTMC patients, central lymph node metastasis (CLNM) is pathologically present. However, clinical risk factors for high-volume CLNM (hv-CLNM) in cN0 PTMC have not been defined well. Therefore, we aimed to obtain evidence for hv-CLNM risk factors in cN0 PTMC. DESIGN: Data on patients who visited our hospital between January 2020 and December 2021 were collected; a preoperative diagnosis of cN0 and a postoperative pathological confirmation of PTMC were obtained. After filtering by inclusion versus exclusion criteria, the obtained data (N = 2268) were included in the meta-analysis. Relevant studies published as of 10 April 2022, were identified from the Web of Science, PubMed, WANFANG, and CNKI databases. These eligible studies were included in the meta-analysis and the association between clinicopathological factors and hv-CLNM in cN0 PTMC was assessed. SPSS and MetaXL were used for statistical analyses. RESULTS: The meta-analysis included 10 previous studies (11,734 patients) and 2268 patients enroled in our hospital for a total of 14,002 subjects. The results of which suggested that younger age (<40, odds ratio [OR] = 3.28, 95% confidence interval [CI] = 2.75-3.92, p < .001 or <45 odds ratio [OR] = 2.93, 95% CI = 2.31-3.72, p < .001), male sex (OR = 2.81, 95% CI = 2.25-3.52, p < .001), tumour size >5 mm (OR = 1.85, 95% CI = 1.39-2.47, p < .001), multifocality (OR = 1.88, 95% CI = 1.56-2.26, p < .001), extrathyroidal extension (OR = 2.58, 95% CI = 2.02-3.30, p < .001), capsule invasion (OR = 2.02, 95% CI = 1.46-2.78, p < .001), microcalcification (OR = 3.25, 95% CI = 2.42-4.36, p < .001) and rich blood flow (OR = 1.65, 95% CI = 1.21-2.25, p = .002) were the significant factors related to an elevated hv-CLNM risk in cN0 PTMC patients. Hashimoto thyroiditis (OR = 0.76, 95% CI = 0.55-1.07, p = .114), irregular margin (versus regular margin, OR = 0.96, 95% CI = 0.68-1.33, p = .787) and hypoechoic (versus nonhypoechoic, OR = 1.27, 95% CI = 0.84-1.92, p = .261) showed no significant association with hv-CLNM. CONCLUSIONS: Younger age, tumour size >5 mm, males, extrathyroidal extension, multifocality, microcalcification, capsular invasion, and rich blood flow were the significant clinicopathological risk factors for hv-CLNM risk in cN0 PTMC patients. These predictors may compensate for the sensitivity of imaging diagnosis in the preoperative period, thus helping in the effective identification of PTMCs with an invasive phenotype.

Predicting peritumoral edema development after gamma knife radiosurgery of meningiomas using machine learning methods: a multicenter study.

OBJECTIVES: Edema is a complication of gamma knife radiosurgery (GKS) in meningioma patients that leads to a variety of consequences. The aim of this study is to construct radiomics-based machine learning models to predict post-GKS edema development. METHODS: In total, 445 meningioma patients who underwent GKS in our institution were enrolled and partitioned into training and internal validation datasets (8:2). A total of 150 cases from multicenter data were included as the external validation dataset. In each case, 1132 radiomics features were extracted from each pre-treatment MRI sequence (contrast-enhanced T1WI, T2WI, and ADC maps). Nine clinical features and eight semantic features were also generated. Nineteen random survival forest (RSF) and nineteen neural network (DeepSurv) models with different combinations of radiomics, clinical, and semantic features were developed with the training dataset, and evaluated with internal and external validation. A nomogram was derived from the model achieving the highest C-index in external validation. RESULTS: All the models were successfully validated on both validation datasets. The RSF model incorporating clinical, semantic, and ADC radiomics features achieved the best performance with a C-index of 0.861 (95% CI: 0.748-0.975) in internal validation, and 0.780 (95% CI: 0.673-0.887) in external validation. It stratifies high-risk and low-risk cases effectively. The nomogram based on the predicted risks provided personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration. CONCLUSION: This RSF model with a nomogram could represent a non-invasive and cost-effective tool to predict post-GKS edema risk, thus facilitating personalized decision-making in meningioma treatment. CLINICAL RELEVANCE STATEMENT: The RSF model with a nomogram built in this study represents a handy, non-invasive, and cost-effective tool for meningioma patients to assist in better counselling on the risks, appropriate individual treatment decisions, and customized follow-up plans. KEY POINTS: • Machine learning models were built to predict post-GKS edema in meningioma. The random survival forest model with clinical, semantic, and ADC radiomics features achieved excellent performance. • The nomogram based on the predicted risks provides personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration and shows the potential to assist in better counselling, appropriate treatment decisions, and customized follow-up plans. • Given the excellent performance and convenient acquisition of the conventional sequence, we envision that this non-invasive and cost-effective tool will facilitate personalized medicine in meningioma treatment.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm.

PURPOSE: Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis. METHODS: Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWISD and ADCSD), DWI and ADC signal intensity ratio (DWISIR and ADCSIR), mean ADC and minimum ADC value (ADCmean and ADCmin) and ADC value standard deviation (ADCVSD). Univariate and multivariate logistic regression were conducted to identify independent predictors, and develop a prediction model. We performed receiver operating characteristic (ROC) analysis to determine the optimal threshold of risk factors, and constructed combined threshold models. Our study calculated diagnostic performance including area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and unnecessary biopsy rate of all models were calculated and compared them with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) result. RESULTS: Two independent predictors of malignant nodules were identified by multivariate analysis: DWISIR (P = 0.007) and ADCmin (P < 0.001). The AUCs for multivariate prediction model, combined DWISIR and ADCmin thresholds model, combined DWISIR and ADCSIR thresholds model and ACR-TIRADS were 0.946 (0.896-0.996), 0.875 (0.759-0.991), 0.777 (0.648-0.907) and 0.722 (0.588-0.857). The combined DWISIR and ADCmin threshold model had the lowest unnecessary biopsy rate of 0%, compared with 56.3% for ACR-TIRADS. CONCLUSION: Quantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.

Study of T2 mapping in quantifying and discriminating uterine lesions under different magnetic field strengths: 1.5 T vs. 3.0 T.

BACKGROUND: MRI is the best imaging tool for the evaluation of uterine tumors, but conventional MRI diagnosis results rely on radiologists and contrast agents (if needed). As a new objective, reproducible and contrast-agent free quantification technique, T2 mapping has been applied to a number of diseases, but studies on the evaluation of uterine lesions and the influence of magnetic field strength are few. Therefore, the aim of this study was to systematically investigate and compare the performance of T2 mapping as a nonenhanced imaging tool in discriminating common uterine lesions between 1.5 T and 3.0 T MRI systems. METHODS: A total of 50 healthy subjects and 126 patients with suspected uterine lesions were enrolled in our study, and routine uterine MRI sequences with additional T2 mapping sequences were performed. T2 maps were calculated by monoexponential fitting using a custom code in MATLAB. T2 values of normal uterine structures in the healthy group and lesions (benign: adenomyosis, myoma, endometrial polyps; malignant: cervical cancer, endometrial carcinoma) in the patient group were collected. The differences in T2 values between 1.5 T MRI and 3.0 T MRI in any normal structure or lesion were compared. The comparison of T2 values between benign and malignant lesions was also performed under each magnetic field strength, and the diagnostic efficacies of the T2 value obtained through receiver operating characteristic (ROC) analysis were compared between 1.5 T and 3.0 T. RESULTS: The mean T2 value of any normal uterine structure or uterine lesion under 3.0 T MRI was significantly lower than that under 1.5 T MRI (p < 0.05). There were significant differences in T2 values between each lesion subgroup under both 1.5 T and 3.0 T MRI. Moreover, the T2 values of benign lesions (71.1 ± 22.0 ms at 1.5 T and 63.4 ± 19.1 ms at 3.0 T) were also significantly lower than those of malignant lesions (101.1 ± 4.5 ms at 1.5 T and 93.5 ± 5.1 ms at 3.0 T) under both field strengths. In the aspect of differentiating benign from malignant lesions, the area under the curve of the T2 value under 3.0 T (0.94) was significantly higher than that under 1.5 T MRI (0.90) (p = 0.02). CONCLUSION: T2 mapping can be a potential tool for quantifying common uterine lesions, and it has better performance in distinguishing benign from malignant lesions under 3.0 T MRI.

Efficient All-Perovskite Tandem Solar Cells with Low-Optical-Loss Carbazolyl Interconnecting Layers.

Combining wide-band gap (WBG) and narrow-band gap (NBG) perovskites with interconnecting layers (ICLs) to construct monolithic all-perovskite tandem solar cell is an effective way to achieve high power conversion efficiency (PCE). However, optical losses from ICLs need to be further reduced to leverage the full potential of all-perovskite tandem solar cells. Here, metal oxide nanocrystal layers anchored with carbazolyl hole-selective-molecules (CHs), which exhibit much lower optical loss, is employed to replace poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT : PSS) as the hole transporting layers (HTLs) in lead-tin (Pb-Sn) perovskite sub-cells and ICLs in all-perovskite tandem solar cells. Optically transparent indium tin oxide nanocrystals (ITO NCs) layers are employed to enhance anchoring of CHs, while a mixture of two CHs is adopted to tune the surface energy-levels of ITO NCs. The optimized mixed Pb-Sn NBG perovskite solar cells demonstrate a high PCE of 23.2 %, with a high short-circuit current density (Jsc ) of 33.5 mA cm-2 . A high PCE of 28.1 % is further obtained in all-perovskite tandem solar cells, with the highest Jsc of 16.7 mA cm-2 to date. Encapsulated tandem solar cells maintain 90 % of their reference point after 500 h of operation at the maximum power point (MPP) under 1-Sun illumination.

An immune-related prognostic signature for thyroid carcinoma to predict survival and response to immune checkpoint inhibitors.

Thyroid carcinoma (THCA) is the most common endocrine malignancy, and its incidence is increasing worldwide. Several studies have explored whether the tumor immune microenvironment and immune-related genes (IRGs) influence the prognosis of patients with THCA and can be used to predict the response to immune checkpoint inhibitors (ICIs). We developed an IRG prognostic/risk signature using a bioinformatics method, and its predictive capacity was validated in patients in the test set and the total set. Subsequently, we analyzed the correlation between this IRG prognostic signature and tumor-infiltrating immune cells, tumor mutation burden (TMB), and immune checkpoint protein expression in patients with THCA. With a multivariate analysis, the IRG prognostic signature, which comprised eight IRGs, was identified as an independent prognostic factor. High-risk patients had poor overall survival compared with low-risk patients. Plasma cells, monocytes, and dendritic cells infiltrated differently according to the IRG prognostic signature. The low-risk group had a higher TMB and immunophenoscore (IPS), which indicated a better response to ICIs. The qRT-PCR validated eight IRGs with differential expression in thyroid cancer and normal tissues. We conclude that the IRG prognostic signature may be a useful tool to predict survival and response to ICIs. However, further testing is required to assess the predictive capacity of this IRG prognostic signature.

Evaluate the immune-related eRNA models and signature score to predict the response to immunotherapy in thyroid carcinoma.

BACKGROUND: The functional alterations of eRNAs have been reported to be correlated with tumorigenesis. However, the roles of eRNAs in thyroid cancer (THCA) remain still unclear. This study aimed to construct an immune-related eRNA prognostic signature that could effectively predict the survival and prognosis for THCA. METHODS: The Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify THCA-specific immune-related hub genes and immune-related eRNAs were obtained using Pearson correlation analysis. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression were conducted to construct an immune-related eRNA prognostic signature in training cohort, and the predictive capability was verified in test cohort and entire cohort. Kaplan-Meier analysis, principal component analysis (PCA), receiver operating characteristic (ROC) curves, and nomogram were used to validate the risk signature. Furthermore, CIBERSORT, ESTIMATE and ssGSEA were analyzed to explore the tumor immune microenvironment (TIME) of the risk signature, and the response of potential immunotherapeutic were also discussed. RESULTS: A total of 125 immune-related eRNAs were obtained and 16 immune-related eRNAs were significantly correlated with overall survival (OS). A 9-immune-related eRNA prognostic signature was constructed, and the risk score was identified as an independent predictor. High-risk groups were associated with a poorer OS. Immune microenvironment analysis indicated that low risk score was correlated with higher immuneScore, high immune cell infiltration, and the better response of immunotherapy. Additionally, we also detected 9 immune-related eRNA expression levels in sixty-two matched tumorous and non-tumorous tissues using qRT-PCR analysis. CONCLUSION: Our immune-related eRNA risk signature that was an independent prognostic factor was strongly correlated with the immune microenvironment and may be promising for the clinical prediction of prognosis and immunotherapeutic responses in THCA patients.

Preliminary Exploration of the Application of Vesical Imaging-Reporting and Data System (VI-RADS) in Post-treatment Patients With Bladder Cancer: A Prospective Single-Center Study.

BACKGROUND: Vesical Imaging-Reporting and Data System (VI-RADS) has been shown to be effective in diagnosing muscle invasion of bladder cancer (BC) in primary patients. PURPOSE: To evaluate the diagnostic efficacy of VI-RADS in a BC target population which included post-treatment patients, and to determine the repeatability. STUDY TYPE: Prospective. POPULATION: Seventy-three patients (42 with primary BC, 31 with post-treatment BC). FIELD STRENGTH/SEQUENCE: 3.0 T MRI with propeller fast spin-echo T2 WI, echo planer imaging diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCEI). ASSESSMENT: VI-RADS scores were independently assessed by five radiologists with different levels of experience. The diagnostic efficiency in each group (primary and post-treatment) and of each radiologist was assessed. STATISTICAL TESTS: Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), and area under the curve (AUC) in receiver operating characteristic curve analysis were calculated to evaluate VI-RADS diagnostic performance. Interobserver agreement was assessed using weighted Kappa statistics. A P value <0.05 was considered statistically significant. RESULTS: At the corresponding cut-off, AUC values of three groups range from 0.936 to 0.947 and AUC values of five observers range from 0.901 to 0.963. There was no significant difference between the AUCs in the primary and post-treatment groups (P = 0.870). The cut-off of the whole group and the post-treatment group was ≥4, and the cut-off of the primary group was ≥3. The Kappa values of interobserver agreements range from 0.709 to 0.923. CONCLUSIONS: After expanding the target population to include post-treatment patients, VI-RADS still has good diagnostic efficacy and repeatability. VI-RADS could potentially be a preoperative staging tool for post-treatment patients. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Highly Ordered Polymer Nanostructures via Solvent On-Film Annealing for Surface-Enhanced Raman Scattering.

Surface-enhanced Raman scattering (SERS) has been a useful sensing technique, in which inelastic light scattering can be significantly enhanced by absorbing molecules onto rough metal surfaces or nanoparticles. Although many methods have been developed to prepare SERS substrates, it is still highly desirable and challenging to design SERS substrates, especially with highly ordered and controlled three-dimensional (3D) structures. In this work, we develop novel SERS substrates with regular volcano-shaped polymer structures using the versatile solvent on-film annealing method. Polystyrene (PS) nanospheres are first synthesized by surfactant-free emulsion polymerization and assembled on poly(methyl methacrylate) (PMMA) films. After annealing in acetic acid vapors, PMMA chains are selectively swollen and wet the surfaces of the PS nanospheres. By selectively removing the PS nanospheres using cyclohexane, volcano-shaped PMMA films can be obtained. Compared with flat PMMA films with water contact angles of ∼74°, volcano-shaped PMMA films exhibit higher water contact angles of ∼110° due to the sharp features and rough surfaces. The volcano-shaped PMMA films are then coated with gold nanoparticles (AuNPs) as SERS substrates. Using rhodamine 6G as the probe molecules, the SERS results show that the Raman signals of the volcano-shaped PMMA/AuNP hybrid substrates are much higher than those of the pristine PMMA films and PMMA films with AuNPs. For the volcano-shaped PMMA/AuNP hybrid substrates using 400 nm PS nanospheres, a high enhancement factor (EF) value of ∼1.12 × 105 with a detection limit of 10-8 M is obtained in a short integration time of 1 s. A linear calibration line with an R2 value of 0.918 is also established, demonstrating the ability to determine the concentrations of the analytes. This work offers significant insight into developing novel SERS substrates, which is crucial for improving the detection limits of analytes.

MRI whole-lesion texture analysis on ADC maps for the prognostic assessment of ischemic stroke.

BACKGROUND: This study aims is to explore whether it is feasible to use magnetic resonance texture analysis (MRTA) in order to distinguish favorable from unfavorable function outcomes and determine the prognostic factors associated with favorable outcomes of stroke. METHODS: The retrospective study included 103 consecutive patients who confirmed unilateral anterior circulation subacute ischemic stroke by computed tomography angiography between January 2018 and September 2019. Patients were divided into favorable outcome (modified Rankin scale, mRS ≤ 2) and unfavorable outcome (mRS > 2) groups according to mRS scores at day 90. Two radiologists manually segmented the infarction lesions based on diffusion-weighted imaging and transferred the images to corresponding apparent diffusion coefficient (ADC) maps in order to extract texture features. The prediction models including clinical characteristics and texture features were built using multiple logistic regression. A univariate analysis was conducted to assess the performance of the mean ADC value of the infarction lesion. A Delong's test was used to compare the predictive performance of models through the receiver operating characteristic curve. RESULTS: The mean ADC performance was moderate [AUC = 0.60, 95% confidence interval (CI) 0.49-0.71]. The texture feature model of the ADC map (tADC), contained seven texture features, and presented good prediction performance (AUC = 0.83, 95%CI 0.75-0.91). The energy obtained after wavelet transform, and the kurtosis and skewness obtained after Laplacian of Gaussian transformation were identified as independent prognostic factors for the favorable stroke outcomes. In addition, the combination of the tADC model and clinical characteristics (hypertension, diabetes mellitus, smoking, and atrial fibrillation) exhibited a subtly better performance (AUC = 0.86, 95%CI 0.79-0.93; P > 0.05, Delong's). CONCLUSION: The models based on MRTA on ADC maps are useful to evaluate the clinical function outcomes in patients with unilateral anterior circulation ischemic stroke. Energy obtained after wavelet transform, kurtosis obtained after Laplacian of Gaussian transform, and skewness obtained after Laplacian of Gaussian transform were identified as independent prognostic factors for favorable stroke outcomes.

Ultrashort time-to-echo T2* and T2* relaxometry for evaluation of lumbar disc degeneration: a comparative study.

BACKGROUND: To compare potential of ultrashort time-to-echo (UTE) T2* mapping and T2* values from T2*-weighted imaging for assessing lumbar intervertebral disc degeneration (IVDD),with Pfirrmann grading as a reference standard. METHODS: UTE-T2* and T2* values of 366 lumbar discs (L1/2-L5/S1) in 76 subjects were measured in 3 segmented regions: anterior annulus fibrosus, nucleus pulposus (NP), and posterior annulus fibrosus. Lumbar intervertebral discs were divided into 3 categories based on 5-level Pfirrmann grading: normal (Pfirrmann grade I),early disc degeneration (Pfirrmann grades II-III), and advanced disc degeneration (Pfirrmann grades IV-V). Regional differences between UTE-T2* and T2* relaxometry and correlation with degeneration were statistically analyzed. RESULTS: UTE-T2* and T2*value correlated negatively with Pfirrmann grades (P < 0.001). In NP, correlations with Pfirrmann grade were high with UTE-T2* values (r = - 0.733; P < 0.001) and moderate with T2* values (r = -0.654; P < 0.001). Diagnostic accuracy of detecting early IVDD was better with UTE-T2* mapping than T2* mapping (P < 0.05),with receiver operating characteristic analysis area under the curve of 0.715-0.876. CONCLUSIONS: UTE-T2* relaxometry provides another promising magnetic resonance imaging sequence for quantitatively evaluate lumbar IVDD and was more accurate than T2*mapping in the earlier stage degenerative process.

Identification and validation of a pyroptosis-related prognostic signature for thyroid cancer.

BACKGROUND: Pyroptosis is a form of programmed cell death triggered by inflammasomes. However, the roles of pyroptosis-related genes in thyroid cancer (THCA) remain still unclear. OBJECTIVE: This study aimed to construct a pyroptosis-related signature that could effectively predict THCA prognosis and survival. METHODS: A LASSO Cox regression analysis was performed to build a prognostic model based on the expression profile of each pyroptosis-related gene. The predictive value of the prognostic model was validated in the internal cohort. RESULTS: A pyroptosis-related signature consisting of four genes was constructed to predict THCA prognosis and all patients were classified into high- and low-risk groups. Patients with a high-risk score had a poorer overall survival (OS) than those in the low-risk group. The area under the curve (AUC) of the receiver operator characteristic (ROC) curves assessed and verified the predictive performance of this signature. Multivariate analysis showed the risk score was an independent prognostic factor. Tumor immune cell infiltration and immune status were significantly higher in low-risk groups, which indicated a better response to immune checkpoint inhibitors (ICIs). Of the four pyroptosis-related genes in the prognostic signature, qRT-PCR detected three of them with significantly differential expression in THCA tissues. CONCLUSION: In summary, our pyroptosis-related risk signature may have an effective predictive and prognostic capability in THCA. Our results provide a potential foundation for future studies of the relationship between pyroptosis and the immunotherapy response.

Ferroptosis-related gene signature predicts the prognosis of papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer (TC), accounting for more than 80% of all cases. Ferroptosis is a novel iron-dependent and Reactive oxygen species (ROS) reliant type of cell death which is distinct from the apoptosis, necroptosis and pyroptosis. Considerable studies have demonstrated that ferroptosis is involved in the biological process of various cancers. However, the role of ferroptosis in PTC remains unclear. This study aims at exploring the expression of ferroptosis-related genes (FRG) and their prognostic values in PTC. METHODS: A ferroptosis-related gene signature was constructed using lasso regression analysis through the PTC datasets of the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the bioinformatics functions of significantly different genes (SDG) of ferroptosis. Additionally, the correlations of ferroptosis and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT database. Finally, SDG were test in clinical PTC specimens and normal thyroid tissues. RESULTS: LASSO regression model was utilized to establish a novel FRG signature with 10 genes (ANGPTL7, CDKN2A, DPP4, DRD4, ISCU, PGD, SRXN1, TF, TFRC, TXNRD1) to predicts the prognosis of PTC, and the patients were separated into high-risk and low-risk groups by the risk score. The high-risk group had poorer survival than the low-risk group (p < 0.001). Receiver operating characteristic (ROC) curve analysis confirmed the signature's predictive capacity. Multivariate regression analysis identified the prognostic signature-based risk score was an independent prognostic indicator for PTC. The functional roles of the DEGs in the TGCA PTC cohort were explored using GO enrichment and KEGG pathway analyses. Immune related analysis demonstrated that the most types of immune cells and immunological function in the high-risk group were significant different with those in the low-risk group. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) verified the SDG have differences in expression between tumor tissue and normal thyroid tissue. In addition, cell experiments were conducted to observe the changes in cell morphology and expression of signature's genes with the influence of ferroptosis induced by sorafenib. CONCLUSIONS: We identified differently expressed FRG that may involve in PTC. A ferroptosis-related gene signature has significant values in predicting the patients' prognoses and targeting ferroptosis may be an alternative for PTC's therapy.

Screening for Early-Stage Parkinson's Disease: Swallow Tail Sign on MRI Susceptibility Map-Weighted Images Compared With PET.

BACKGROUND: Swallow tail sign (STS) on MRI is presumed to be an imaging biomarker of nigrosome-1, which may exhibit a similar role as positron emission tomography (PET), indicating dopaminergic degeneration. PURPOSE: To investigate whether an alteration of STS could serve as an alternative screening sign compared with PET in the diagnosis of early-stage Parkinson's disease (esPD). STUDY TYPE: Prospective. POPULATION: Thirty-seven patients with esPD and 27 age- and sex-matched healthy controls (HCs). FIELD STRENGTH/SEQUENCE: Quantitative susceptibility mapping images were collected on 3T MRI and [18 F]9-fluoropropyl-(+)-dihydrotetra-benazine PET images were acquired using a 64 rings PET/CT scanner. ASSESSMENT: Alterations of STS and striatal uptake in each hemisphere were visually rated on a 0-2 points scale. Point 2: normal appearance of STS/normal striatal uptake; Point 1: partial loss of STS/uptake reduction confined to the putamen; Point 0: total loss of STS/uptake reduction extended to the caudate nucleus. The concordance rate of STS rating and ipsilateral striatal binding was calculated at the nuclei level. At the participant level, an evaluation rating was calculated by adding the STS ratings from both hemispheres to distinguish esPD from HCs. STATISTICAL TESTS: The intra- and interobserver agreement were tested using Cohen's kappa and the intraclass correlation coefficient. Hotelling's T-squared test was used to compare the difference of rating points. Receiver operating characteristic analysis was performed to evaluate the diagnostic power. RESULTS: The intra- and interobserver agreement for STS and striatal uptake rating was over 0.75. There was no significant difference of rating point distribution (P = 0.084). The concordance rate was 94.3% for the right side and 91.4% for the left. Using bilateral partial loss of STS as the threshold, the achieved sensitivity and specificity for discriminating esPD from HCs were 94.59% and 92.49%, respectively. DATA CONCLUSION: STS alterations corresponded well with striatal uptake on PET in esPD, and our proposed evaluation scale of STS had satisfactory diagnostic performance in discriminating the disease. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Condition-Specific Molecular Network Analysis Revealed That Flagellar Proteins Are Involved in Electron Transfer Processes of Shewanella piezotolerans WP3.

Because of the ability to metabolize a large number of electron acceptors such as nitrate, nitrite, fumarate, and metal oxides, Shewanella species have attracted much attention in recent years. Generally, the use of these electron acceptors is mainly achieved through electron transfer proteins and their interactions which will dynamically change across different environmental conditions in cells. Therefore, functional analysis of condition-specific molecular networks can reveal biological information on electron transfer processes. By integrating expression data and molecular networks, we constructed condition-specific molecular networks for Shewanella piezotolerans WP3. We then identified condition-specific key genes and studied their potential functions with an emphasis on their roles in electron transfer processes. Functional module analysis showed that different flagellar assembly modules appeared under these conditions and suggested that flagellar proteins are important for these conditions. We also identified the electron transfer modules underlying these various environmental conditions. The present results could help with screening electron transfer genes and understanding electron transfer processes under various environmental conditions for the Shewanella species.

Swallow tail sign on susceptibility map-weighted imaging (SMWI) for disease diagnosing and severity evaluating in parkinsonism.

BACKGROUND: Loss of swallow tail sign (STS) on iron-sensitive magnetic resonance imaging (MRI) has been recognized as an imaging feature in parkinsonism (PS). PURPOSE: To investigate the diagnostic and differential diagnostic value of STS scale on susceptibility map-weighted imaging (SMWI) in PS, including Parkinson's disease (PD), progressive supranuclear palsy syndrome (PSP), and multiple system atrophy (MSA), and to evaluate its correlation with disease severity. MATERIAL AND METHODS: Ninety-nine patients (55 PD, 29 PSP, and 15 MSA) and 47 healthy controls (HC) were prospectively recruited and scanned using quantitative susceptibility mapping (QSM). STS was visually assessed on SMWI derived from QSM. STS scale in the range of 0-4 at participant level was calculated by summing bilateral STS scores (0-2). We used receiver operating characteristic analysis of STS scale for evaluating the diagnostic power of parkinsonism and Spearman's correlation for assessing disease severity. RESULTS: Frequency distribution of STS scale was significantly different in parkinsonism and HC groups, and among PD, PSP, and MSA subgroups. STS scale ≤3 could distinguish parkinsonism from HC with high accuracy (91.78%), PD from HC (91.18%), and MSA from HC (88.71%). STS scale ≤2 could distinguish PSP from HC (96.05%). STS scale = 0 could distinguish PSP from PD (70.24%) and PSP from MSA (72.73%). STS scale was negatively correlated with H-Y stage (P = 0.007, r = -0.359) and duration of disease (P = 0.006, r = -0.367) in PD patients. CONCLUSION: STS scale on SMWI may serve as a useful imaging biomarker for diagnosis of parkinsonism and disease progression evaluation in PD.